Development of Spectral Signature of Chir Pine Using Hyperion Data

Abstract

The study was conducted during January, 2023 which aims to map the chir pine forest of the Almora region of Uttarakhand, India using hyperion data and construct a spectral signature. The data was processed using ENVI 4.4 software. For image classification, the Spectral Angle Mapper (SAM) was employed. Many remote sensing projects covering relatively large areas have effectively exploited multispectral data for data extraction and statistical analysis of natural resources. Hyperspectral imagery has seen recent methodological and technological developments that open up new avenues for researching the structure and processes of local ecosystems. Within the realm of sustainability studies, trees are deemed essential for a multitude of ecosystem services that encompass environmental quality, food security, and human health. Species level tree mapping could be one of these prerequisites. Using a reliable method for species-level remote sensing of forest composition will significantly advance our understanding of these dynamics. After the correct match between field spectra and pixel spectra was established, the spectra library of chir pine was created. The result show that the NIR spectral range (700–1300 nm) has higher spectral reflectance than the visible region (400–700 nm). The data indicated a sharp decrease shortly after 1300 and 1700 nm. The library of spectral signature created for the chir pine will serve as the target spectrum for the classification of remote sensing data pertaining to this species. With this knowledge, there may be considerable opportunity to support upcoming initiatives aimed at sustainability in various socio-ecological contexts.